Optical mark scanning apparatus (hereinafter referred to as optical mark reading or OMR systems) are well known in the prior art. There are a wide variety of applications that use OMR systems and scannable forms in the large-scale gathering of discrete pieces of information recorded on documents (e.g., scores from standardized tests, census information, preference surveys, etc.). OMR systems generally sense data recorded with marks containing pigment that absorbs light in the near infrared (NIR) range (e.g., marks from a No. 2 pencil or other marker containing graphite or other form of carbon) in specific, predefined fields on a form. Such data are position-encoded, in that their meaning is interpreted based on where the data has been marked on the form document used to record it. This is called NIR-mode scanning. A primary advantage of NIR-mode scanning (or other scanning based on limited spectral responsivity) is that it allows separation of the respondent-marked variable data from the standard background printing on the same document.
Although a more recent development, visual image scanning apparatus (hereinafter referred to as VIS mode scanners or VIS systems) are also well known in the prior art. Most of the applications for current VIS systems have developed out of the desire to find replacements for traditional microfilm image capture systems. As a result, the focus of current VIS systems is on the acquisition of the total scanned image of a document, as compared to the detection, dark mark resolution and processing of discrete pieces of information recorded in predefined fields done by current OMR systems.
One of the limitations with current OMR systems that focus on predefined fields is their lack of any ability to scan or reproduce the context of a scannable form surrounding the predefined fields. As a result, the retrieval and viewing or hard copy replication of the stored or archived discrete, raw information from a form scanned by an OMR system is of limited value, because there is no capability for interpreting that information without resorting to the form, a transparent overlay or even a booklet associated with the form, as is the case in standardized testing.
VIS systems, on the other hand, are capable of reproducing the entire contents of a scannable form (both standard background printing and any variable data) as a digitized, pixel image, but any associated OMR processing logic cannot easily interpret or analyze any of the discrete, variable information contained in a VIS-mode pixel image of the form. A great deal of digitized data both fixed and variable, can be collected by VIS images, but the meaning of the variable data remains to be extracted and not all of the VIS-mode data collected may be of interest. For example, if an 81/2".times.11" piece of paper is scanned at a resolution of 120 dots per inch (DPI), vertically and horizontally, and with an eight-bit grayscale range, more than 1.3 megabytes worth of bit-level scanned information may be generated from this single page. Obviously, a tremendous amount of computer processing power may be necessary to extract and analyze significant bit-level information or even localized pixel segments (often called regions of interest or areas of interest (AOI's) from a form scanned with a VIS system. Moreover, the storage requirements for storing all of this information in a situation where hundreds or thousands of documents are being processed to capture a complete pixel image as a by-product of capturing the variable data is so large as to be prohibitively expensive in most applications.
One approach that has been used to reduce the amount of data that must be stored when documents containing text and/or numbers are VIS scanned is to use symbol recognition systems (usually computer-based) to convert the visual image of text and/or numbers into more-compact, character-based alphanumeric data. The latter requires far less memory for storage and has the further advantage that it can be used as an input file for a word processing program, a text search program, or a variety of other software for manipulating files consisting of text and/or numerical data.
The manner in which information is recorded or encoded on a document is, in the present state of technology, highly determinative of the speed and accuracy with which computer-based systems can extract the information and convert it into digital form. Present technology offers no very effective way of converting text that is handwritten in script into digital form. Handprinted information can be interpreted and converted into digital form with some degree of success, particularly if the symbol recognition processor is highly adaptive, such as a neural network. This task is easiest when the information involved is numerical, because this sharply reduces the universe of characters to be recognized. Other forms of encoding information permit symbol recognition and conversion into digital data with greater ease. Bar code recognition is now an advanced art and widely used to identify products in manufacturing, distribution and sales. Optical character recognition of certain printed fonts is also advanced to the point where speedy, accurate translation from printed information to digitally-stored alphanumeric data is possible. OMR scanning, mentioned above, is a further highly developed art that permits rapid translation of position encoded data from document form to character-based alphanumeric form.
Having all these options before them, persons who wish to collect information by having it recorded on documents now have the ability to design a document that combines one or more of the above forms of data representation. To the extent that the document incorporates several different forms of data representation, new problems are raised concerning how the documents can rapidly be converted into character-based data by automated means. Moreover, to the extent such a document permits some data to be recorded by hand marking or hand writing, some recorded information will be ambiguous under the criteria defined by the automated symbol recognition systems employed to interpret the information (e.g., faint OMR marks, heavy smudges or erasures, badly reproduced OCR font print, careless hand printing) and other recorded information will be either beyond the capacities of the available symbol recognition technology (e.g., handwritten script entries) or may only have significance in its full, undigested, visual form (e.g., a signature or a sketch).
What is needed is a document scanning system and method that permits information encoded in a wide variety of ways to be efficiently processed so as to extract the desired information, where possible, in character-based alphanumeric form, while preserving the option to retain all or portions of such information in "electronic-image" visual form for examination by a human operator.